學術報告
題目：SLRTA: A Sparse and Low-Rank Tensor-based Approach to Internet Traffic Anomaly Detection Lyapunov stability versus Jacobi stability
報告人：羅自炎，教授，北京交通大學
地點：騰訊會議（ID：882 713 363）
時間：2021年3月16日，8:30-11:30
摘要：Internet traffic anomaly detection (ITAD) is a critical task for various network tasks such as traffic engineering and network security. Traditional matrix-based approaches of ITAD have limitations for traffic data with multi-way structures, while the emerging tensor-based approaches of ITAD lack of sufficient consideration for circumstances including incomplete measurements or link-load measurements. To address these issues, we formulate ITAD by a sparse low-rank tensor optimization model, taking into full consideration the intrinsic and potential properties including the sparsity of anomalies, the low-rankness and temporal stability and periodicity of the normal traffic data. Although the resulting optimization model is non-convex and discontinuous due to the involved L0-norm and the tensor rank function, optimality analysis via stationarity is established, based on which an efficient proximal gradient method with theoretical convergence to stationary points is designed. Numerical experiments on Internet traffic trace data Abilene and GEANT demonstrate the high efficiency of our proposed sparse and low-rank tensor-based approach (SLRTA) for ITAD.
報告人簡介
羅自炎，女，北京交通大學理學院教授、博士生導師。2010年獲北京交通大學理學院運籌學與控制論專業博士學位，美國Stanford大學管理與科學工程系、新加坡國立大學、英國南安普頓大學訪問學者、香港理工大學應用數學系研究助理。主要從事大規模統計優化算法設計、稀疏與低秩優化、張量分析與張量理論等方面的研究。共發表SCI檢索期刊論文30余篇，其中ESI高被引論文2篇。撰寫英文專著1部，由國際著名SIAM出版社于2017年4月出版，編寫中文著作《半定規劃》, 已被國內多所高校的優化專業選為研究生教材。主持國家自然科學基金面上項目、國家自然科學基金重點項目子課題、國家自然科學基金青年基金項目、北京市自然科學基金重點項目各1項。2016年在北京運籌學年會上做大會特邀報告，2017年在第十一屆全國數學規劃學術會議上做青年專題報告，2020年獲中國運籌學會青年科技獎提名獎。
